Kmer-SSR: a fast and exhaustive SSR search algorithm

Abstract

MotivationOne of the main challenges with bioinformatics software is that the size and complexity of datasets necessitate trading speed for accuracy, or completeness. To combat this problem of computational complexity, a plethora of heuristic algorithms have arisen that report a ‘good enough’ solution to biological questions. However, in instances such as Simple Sequence Repeats (SSRs), a ‘good enough’ solution may not accurately portray results in population genetics, phylogenetics and forensics, which require accurate SSRs to calculate intra- and inter-species interactions.ResultsWe present Kmer-SSR, which finds all SSRs faster than most heuristic SSR identification algorithms in a parallelized, easy-to-use manner. The exhaustive Kmer-SSR option has 100% precision and 100% recall and accurately identifies every SSR of any specified length. To identify more biologically pertinent SSRs, we also developed several filters that allow users to easily view a subset of SSRs based on user input. Kmer-SSR, coupled with the filter options, accurately and intuitively identifies SSRs quickly and in a more user-friendly manner than any other SSR identification algorithm.Availability and implementationThe source code is freely available on GitHub at https://github.com/ridgelab/Kmer-SSR.

Transcriptome Comparison of Rhizome and Leaf of Rhizome of Ligusticum Chuanxiong on the Effects of Active Metabolites

“…In recent years, with the development of high-throughput sequencing technology and the reduction of the cost of second-generation sequencing as well as the update of SSR development software, SSRs for medicinal plants have been developed and applied [35] . Since SSRs have interspeci c variability, we were able to use some high-frequency SSRs as biomarkers for interspeci c kinship analysis of Ligusticum chuanxiong.…”

SSRMMD: A Rapid and Accurate Algorithm for Mining SSR Feature Loci and Candidate Polymorphic SSRs Based on Assembled Sequences

“…Perfect repeats have higher allelic variability than imperfect repeats, and any SSR used to develop genetic markers should contain a perfect repeat ( Xu et al, 2013 ). Therefore, to assess the potential of SSRMMD for mining SSR loci, we avoided imperfect repeats detection tools, and we selected six popular existing software programs including SSRIT ( Temnykh, 2001 ), MISA ( Thiel et al, 2003 ), GMATA ( Wang and Wang, 2016 ), SA-SSR ( Pickett et al, 2016 ), Kmer-SSR ( Pickett et al, 2017 ), and PERF ( Avvaru et al, 2017 ). In particular, SA-SSR was not included in the results owing to its markedly low computational speed.…”

“…SA-SSR (Pickett et al, 2016) uses a suffix array-based algorithm to mine SSRs. Kmer-SSR (Pickett et al, 2017) uses Kmer decomposition to identify SSRs. PERF (Avvaru et al, 2017) matches each potential substring in accordance with a set of pre-computed repeat strings.…”

IDSSR: An Efficient Pipeline for Identifying Polymorphic Microsatellites from a Single Genome Sequence

“…To date, more than 25 tools or methods are available for identifying microsatellites from genome or RNA sequences, and this number is increasing [10,11,12]. These tools, such as Tandem Repeat Finder (TRF) [13], GMATo [14], SSRIT [15], SSR-pipeline [16], MREPS [17], PRoGeRF [18], MISA [19], Kmer-SSR [20], ESAP plus [21], SA-SRR [22], PERF [23], and SciRoko [24], are used to conduct SSR mining. In contrast, other tools such as SSRLocator [25], QDD [26], CandiSRR [27], GMATA [28], and SSRPoly [29] have been improvised with the inclusion of a primer design algorithm.…”